breeze.optimize

OWLQN

class OWLQN[T] extends LBFGS[T] with SerializableLogging

Implements the Orthant-wise Limited Memory QuasiNewton method, which is a variant of LBFGS that handles L1 regularization.

Paper is Andrew and Gao (2007) Scalable Training of L1-Regularized Log-Linear Models

Linear Supertypes
LBFGS[T], FirstOrderMinimizer[T, DiffFunction[T]], SerializableLogging, Serializable, Serializable, Minimizer[T, DiffFunction[T]], AnyRef, Any
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Inherited
  1. OWLQN
  2. LBFGS
  3. FirstOrderMinimizer
  4. SerializableLogging
  5. Serializable
  6. Serializable
  7. Minimizer
  8. AnyRef
  9. Any
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Visibility
  1. Public
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Instance Constructors

  1. new OWLQN(maxIter: Int, m: Int, l1reg: Double = 1.0, tolerance: Double = 1.0E-8)(implicit vspace: MutableCoordinateSpace[T, Double])

Type Members

  1. type History = ApproximateInverseHessian[T]

    Definition Classes
    LBFGS → FirstOrderMinimizer

  2. case class State(x: T, value: Double, grad: T, adjustedValue: Double, adjustedGradient: T, iter: Int, initialAdjVal: Double, history: History, fVals: IndexedSeq[Double] = ..., numImprovementFailures: Int = 0, searchFailed: Boolean = false) extends Product with Serializable

    Definition Classes
    FirstOrderMinimizer

Value Members

  1. final def !=(arg0: AnyRef): Boolean

    Definition Classes
    AnyRef

  2. final def !=(arg0: Any): Boolean

    Definition Classes
    Any

  3. final def ##(): Int

    Definition Classes
    AnyRef → Any

  4. final def ==(arg0: AnyRef): Boolean

    Definition Classes
    AnyRef

  5. final def ==(arg0: Any): Boolean

    Definition Classes
    Any

  6. def adjust(newX: T, newGrad: T, newVal: Double): (Double, T)

    Attributes
    protected
    Definition Classes
    OWLQN → FirstOrderMinimizer

  7. def adjustFunction(f: DiffFunction[T]): DiffFunction[T]

    Attributes
    protected
    Definition Classes
    LBFGS → FirstOrderMinimizer

  8. final def asInstanceOf[T0]: T0

    Definition Classes
    Any

  9. def calculateObjective(f: DiffFunction[T], x: T, history: History): (Double, T)

    Attributes
    protected
    Definition Classes
    FirstOrderMinimizer

  10. def chooseDescentDirection(state: State, fn: DiffFunction[T]): T

    Attributes
    protected
    Definition Classes
    OWLQN → LBFGS → FirstOrderMinimizer

  11. def clone(): AnyRef

    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

  12. def determineStepSize(state: State, f: DiffFunction[T], dir: T): Double

    Given a direction, perform a line search to find a direction to descend.

    Given a direction, perform a line search to find a direction to descend. At the moment, this just executes backtracking, so it does not fulfill the wolfe conditions.

    state

    the current state

    f

    The objective

    dir

    The step direction

    returns

    stepSize

    Attributes
    protected
    Definition Classes
    OWLQN → LBFGS → FirstOrderMinimizer

  13. final def eq(arg0: AnyRef): Boolean

    Definition Classes
    AnyRef

  14. def equals(arg0: Any): Boolean

    Definition Classes
    AnyRef → Any

  15. def finalize(): Unit

    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( classOf[java.lang.Throwable] )

  16. final def getClass(): Class[_]

    Definition Classes
    AnyRef → Any

  17. def hashCode(): Int

    Definition Classes
    AnyRef → Any

  18. def initialHistory(f: DiffFunction[T], x: T): History

    Attributes
    protected
    Definition Classes
    LBFGS → FirstOrderMinimizer

  19. def initialState(f: DiffFunction[T], init: T): State

    Attributes
    protected
    Definition Classes
    FirstOrderMinimizer

  20. final def isInstanceOf[T0]: Boolean

    Definition Classes
    Any

  21. def iteratingShouldStop(state: State): Boolean

    Definition Classes
    FirstOrderMinimizer

  22. def iterations(f: DiffFunction[T], init: T): Iterator[State]

    Definition Classes
    FirstOrderMinimizer

  23. def logger: Logger

    Definition Classes
    SerializableLogging

  24. val minImprovementWindow: Int

    Definition Classes
    FirstOrderMinimizer

  25. def minimize(f: DiffFunction[T], init: T): T

    Definition Classes
    FirstOrderMinimizer → Minimizer

  26. final def ne(arg0: AnyRef): Boolean

    Definition Classes
    AnyRef

  27. final def notify(): Unit

    Definition Classes
    AnyRef

  28. final def notifyAll(): Unit

    Definition Classes
    AnyRef

  29. val numberOfImprovementFailures: Int

    Definition Classes
    FirstOrderMinimizer

  30. final def synchronized[T0](arg0: ⇒ T0): T0

    Definition Classes
    AnyRef

  31. def takeStep(state: State, dir: T, stepSize: Double): T

    Attributes
    protected
    Definition Classes
    OWLQN → LBFGS → FirstOrderMinimizer

  32. def toString(): String

    Definition Classes
    AnyRef → Any

  33. def updateFValWindow(oldState: State, newAdjVal: Double): IndexedSeq[Double]

    Attributes
    protected
    Definition Classes
    FirstOrderMinimizer

  34. def updateHistory(newX: T, newGrad: T, newVal: Double, f: DiffFunction[T], oldState: State): History

    Attributes
    protected
    Definition Classes
    LBFGS → FirstOrderMinimizer

  35. final def wait(): Unit

    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

  36. final def wait(arg0: Long, arg1: Int): Unit

    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

  37. final def wait(arg0: Long): Unit

    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

Inherited from LBFGS[T]

Inherited from FirstOrderMinimizer[T, DiffFunction[T]]

Inherited from SerializableLogging

Inherited from Serializable

Inherited from Serializable

Inherited from Minimizer[T, DiffFunction[T]]

Inherited from AnyRef

Inherited from Any

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